Search and Predictability of Prices in the Housing Market

Author:

Møller Stig Vinther12ORCID,Pedersen Thomas12ORCID,Montes Schütte Erik Christian12ORCID,Timmermann Allan34ORCID

Affiliation:

1. Department of Economics and Business Economics, Aarhus University, 8210 Aarhus, Denmark;

2. Danish Finance Institute, 2000 Frederiksberg, Denmark;

3. University of California, San Diego, La Jolla, California 92093;

4. Center for Economic and Policy Research, London EC1V 0DX, United Kingdom

Abstract

We develop a new housing search index (HSI) extracted from online search activity on a limited set of keywords related to the house-buying process. We show that HSI has strong predictive power over subsequent changes in house prices, both in-sample and out-of-sample and after controlling for the effect of commonly used predictors, and relate our findings to models of search-induced frictions. Our results imply that search data can be used as an early indicator of where the market is going. This paper was accepted by David Sraer, finance. Funding: We acknowledge support from the Danish Finance Institute and from the Independent Research Fund Denmark [Grants DFF 7024-00020B and DFF 7015-00017B]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4672 .

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

Management Science and Operations Research,Strategy and Management

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